Technological progress in the field of optical image acquisition allows the use of camera-based driver assistance systems which are located behind the windshield and capture the area in front of the vehicle in the way the driver perceives it. The functionality of these systems ranges from automatic headlights to the detection and display of speed limits, lane departure warnings, and imminent collision warnings.
Starting from just capturing the area in front of the vehicle to a full 360° panoramic view, cameras can now be found in various applications and different functions for driver assistance systems in modern vehicles. It is the primary task of digital camera image processing as a standalone function or in conjunction with radar or lidar sensors to detect, classify, and track objects in the image section. Classic objects typically include various vehicles such as cars, trucks, two-wheel vehicles, or pedestrians. In addition, cameras detect traffic signs, lane markings, guardrails, free spaces, or other generic objects.
Automatic learning and detection of object categories and their instances is one of the most important tasks of digital image processing and represents the current state of the art. Due to the methods which are now very advanced and which can perform these tasks almost as well as a person, the focus has now shifted from a coarse localization to a precise localization of the objects.
Modern driver assistance systems use different sensors including video cameras to capture the area in front of the vehicle as accurately and robustly as possible. This environmental information, together with driving dynamics information from the vehicle (e.g. from inertia sensors) provide a good impression of the current driving state of the vehicle and the entire driving situation. This information can be used to derive the criticality of driving situations and to initiate the respective driver information/alerts or driving dynamic interventions through the brake and steering system.
However, since the available friction coefficient or road condition is not provided or cannot be designated in driver assistance systems, the times for issuing an alert or for intervention are in principle determined based on a dry road with a high adhesion coefficient between the tire and the road surface. This results in the problem that accident-preventing or at least impact-weakening systems warn the driver or intervene so late that accidents are prevented or accident impacts acceptably weakened only if the road is really dry. If, however, the road provides less adhesion due to moisture, snow, or even ice, an accident can no longer be prevented and the reduction of the impact of the accident does not have the desired effect.